目标检测发展线路图–https://github.com/hoya012/deep_learning_object_detection
车辆检测竞赛
http://detrac-db.rit.albany.edu/DetRet 检测
http://detrac-db.rit.albany.edu/Tracking 跟踪
车辆检测
Evolving Boxes for Fast Vehicle Detection ICME 2017
http://zhengyingbin.cc/EvolvingBoxes/
https://github.com/Willy0919/Evolving_Boxes
车辆检测
Small U-Net for vehicle detection
https://github.com/vxy10/p5_VehicleDetection_Unet
目标检测 Faster RCNN + SSD
Single-Shot Refinement Neural Network for Object Detection
https://github.com/sfzhang15/RefineDet
目标检测
A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection ECCV2016
https://github.com/zhaoweicai/mscnn
目标检测 — 加速候选区域提取
DeNet: Scalable Real-time Object Detection with Directed Sparse Sampling ICCV2017
https://github.com/lachlants/denet
【Dlib 19.5车辆检测】《Vehicle Detection with Dlib 19.5》
http://blog.dlib.net/2017/08/vehicle-detection-with-dlib-195_27.html
目标检测
RON: Reverse Connection with Objectness Prior Networks for Object Detection CVPR2017
https://github.com/taokong/RON
同时检测和分割，类似 Mask R-CNN
BlitzNet: A Real-Time Deep Network for Scene Understanding ICCV2017
https://github.com/dvornikita/blitznet
目标检测
DSOD: Learning Deeply Supervised Object Detectors from Scratch ICCV2017
https://github.com/szq0214/DSOD
目标检测：
PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection
https://github.com/sanghoon/pva-faster-rcnn
目标检测
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/daijifeng001/r-fcn
目标检测
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection CVPR 2017
Caffe code : https://github.com/xiaolonw/adversarial-frcnn
目标检测
Improving Object Detection With One Line of Code
https://github.com/bharatsingh430/soft-nms
行人检测：
Is Faster R-CNN Doing Well for Pedestrian Detection？ ECCV2016
https://github.com/zhangliliang/RPN_BF/tree/RPN-pedestrian
检测
Accurate Single Stage Detector Using Recurrent Rolling Convolution
https://github.com/xiaohaoChen/rrc_detection